Assessment of genetic diversity and volatile content of commercially grown banana (Musa spp.) cultivars

Banana is an important fruit crop in the tropics and subtropics; however, limited information on biomarkers and signature volatiles is available for selecting commercial cultivars. Clonal fidelity is a major contributor to banana yield and aroma; however, there are no useful biomarkers available to validate clonal fidelity. In this study, we performed the molecular profiling of 20 banana cultivars consisting of diploid (AA or AB) and triploid (AAA or AAB or ABB) genomic groups. We screened 200 molecular markers, of which 34 markers (11 RAPD, 11 ISSR, and 12 SSR) yielded unequivocally scorable biomarker profiles. About 75, 69, and 24 allelic loci per marker were detected for RAPD, ISSR, and SSR markers, respectively. The statistical analysis of molecular variance (AMOVA) exhibited a high genetic difference of 77% with a significant FST value of 0.23 (p < 0.001). Interestingly, the UBC-858 and SSR CNMPF-13 markers were unique to Grand Nain and Ardhapuri cultivars, respectively, which could be used for clonal fidelity analysis. Furthermore, the analysis of banana fruit volatilome using headspace solid-phase microextraction-gas chromatography-tandem mass spectrometry (HS-SPME-GCMS) revealed a total of fifty-four volatile compounds in nine banana cultivars with 56% of the total volatile compounds belonging to the ester group as the significant contributor of aroma. The study assumes significance with informative biomarkers and signature volatiles which could be helpful in breeding and for the authentic identification of commercial banana cultivars.


Materials and methods
Plant genetic resources. The leaf samples of twenty different germplasm of banana comprising diploid and triploid genomes were collected from the Banana Research Station, Nanded affiliated to Vasantrao Naik Marathwada Krishi Vidyapeeth (VNMKV), Parbhani ( Table 1). The study complies with relevant institutional biosafety regulations and guidelines. The genomic DNA was extracted using the modified CTAB method 27 followed by RNase treatment. The qualitative and quantitative analysis of genomic DNA was done using a spectrophotometer and by resolving on 0.8% agarose gel. The Genomic DNA was diluted to 50 ng/µL and subsequently used for RAPD, ISSR, and SSR fingerprint analysis. RAPD, ISSR, and SSR genotyping. A total of 200 primers were used for pre-screening and of which 11 RAPD, 11 ISSR, and 12 SSR primers were used for genotyping twenty banana cultivars ( Table 2). Banana cultivars representing each genome type i.e. Namarai from diploid, Birbutia and Grand Nain from triploid, and NRCB-3 from tetraploid were selected for pre-screening. Among the 75 RAPD, 60 ISSR and 65 SSR primers; the primers showing amplification in the all above selected banana cultivars were shortlisted. PCR reactions for RAPD genotyping were carried out in 25.0 µL reaction volume containing 2.5 µL 10× PCR assay buffer with MgCl 2 (10×), 0.5 µL dNTP mix (10 mM), 0.33 µL Taq DNA polymerase (3 U/µL), 2 µL Primer (10 µm/µL) and 1 µL template DNA (50 ng/µL). ISSR PCR reaction of 25.0 µL comprised 2.5 µL 10× PCR assay buffer with MgCl 2 , 0.5 µL dNTP mix (10 mM), 0.4 µL Taq DNA polymerase (3 U/µL), 1 µL Primer (10 µm/µL) and 1 µL template DNA (50 ng/µL). The SSR genotyping were performed in 25.0 µL reaction with 2.5 µL 10× PCR assay buffer, 1.5 µL MgCl 2 (25 mM) , 0.5 µL dNTP mix (10 mM), 0.5 µL Taq DNA polymerase (3 U/µL), 1.5 µL each forward and reverse primer (10 µm/µL) and 1.5 µL template DNA (50 ng/µL). The RAPD PCR was carried out in Eppendorf thermal cycler for 5 min at 94 °C, followed by 40 cycles of 45 s at 94 °C, 1 min at 36 °C, 1 min at 72 °C with a final extension time of 10 min at 72 °C. The thermal cycler conditions for ISSR genotyping were initial denaturation at 94 °C for 5 min followed by 40 cycles of 45 s at 94 °C, 1 min at 52 °C, 1 min at 72 °C with a final extension time of 10 min at 72 °C. A thermal cycler for SSR PCR was carried out at 94 °C for 4 min, 35 cycles of 94 °C for 40 s, 54 °C for 30 s, and 72 °C for 40 s followed by a final extension of 10 min at 72 °C. The RAPD and ISSR PCR amplified products were resolved on 1.5% agarose gel at 100 V. Whereas, SSR PCR products were resolved on 2.5% agarose gel at 100 V, followed by ethidium bromide staining. The images were captured by a gel documentation system (AlphaImager, TM-2200). www.nature.com/scientificreports/ Data scoring and analysis. All visible and unambiguously scorable fragments amplified by the RAPD, ISSR, and SSR primers were scored as scorable fragments. Amplification profiles of the germplasm were compared, and bands of DNA fragments were scored as present (1) or absent (0). The DNA fingerprint data of the primers were utilized to estimate genetic similarity based on a number of shared amplification products 28 . The equation used was the number of shared amplification products = 2 × (number of typical bands between any two lanes)/(Total number of bands in the same two lanes). Genetic relationship among the germplasm was estimated with the dendrogram constructed through an unweighted pair group of arithmetic means using (UPGMA) 29 and NTSYS pc 2.02 software. Further, the population genetic structure was analyzed based on SSR amplicons score as allele size (bp) using the Bayesian clustering method and STRU CTU RE v.v 2.3.3 software 30 . The admixture model and correlated allele frequencies were applied for the estimation of ancestry fractions of each cluster. The value of K (range 1-10) was estimated using five independent runs and a burn-in period of 20,000 followed by 200,000 MCMC (Markov Chain Monte Carlo) repetitions. The web-based software STRU CTU RE HARVESTER version 0.6.92 was used to determine the optimum K value using the log probability of data, LnP(D) based on the rate of change in LnP(D) between successive K 31 .
Volatile profiling of Banana cultivars using HS-SPME GCMS. The unripe banana fruits of available banana cultivars were collected from the Banana Research Station, Nanded, and kept for ripening at 20 °C.The pulp of fully ripe banana fruits was used for volatile analysis. A blended pulp juice from the three banana fruits of each banana cultivar was prepared separately, and 16 g of juice in a 30 ml glass vial tightly sealed with a Teflon septum with a plastic cap was used for volatile analysis. Optimized SPME parameters, i.e., sample equilibration for 15 min, adsorption for 60 min at 25 °C, and desorption time of 10 min, were used for GCMS sampling 32 . The 430 GC analyzed the volatile compounds, and 210 MS (Varian) gas chromatograph-mass spectrometer (GC-MS) equipped VF-5 MS column with helium as the carrier gas at a flow rate of 1.0 mL/min was used for detection of m/z ratio of fragmented ions and derived spectrum. The injection port was lined with a 0.75 mm, i.e., splitless glass inserter, and maintained at 200 °C. The oven temperature was programmed to rise from 50 to150 °C at 2 °C/min and the total GC run time was 55 min. MS transfer line was maintained at 290 °C, ionization energy was 70 eV, and the mass range was 50-550 m/z. The volatile compounds were identified by comparing the results obtained with the reference mass spectra from the NIST library (NIST98, version 2.0, Gaithersburg, USA) and retention index values obtained using a standard mixture of alkanes (C8-C20).

Results
Various molecular markers have been used extensively to screen the diversity and develop biomarkers for clonal identity in crops, including banana 9,17,33 . Here we employed three different markers-RAPD, ISSR, and SSR to search the cultivar-specific biomarkers. The molecular marker provided genetic information and assisted in finding out biomarkers specific to Grand Nain and Ardhapuri cultivars. Additionally, we performed the volatile profiling of banana cultivars to characterize the compounds that contribute to the characteristic aroma of the banana fruits.  www.nature.com/scientificreports/ OPN-02, each with 08 allelic loci. We evaluated the allele size of the RAPD profile, and it ranged from 0.1 to 1.5 kb. The polymorphic information content (PIC) value ranged from 0.43 for OPA-17 and OPA-10 to 0.25 for OPA-11 (Table 3). Furthermore, the average Shannon's diversity index (H), expected heterozygosity (He), resolution power (RP), and marker index (MI) values for RAPD primers were 0.53, 0.35, 7.11, and 2.62, respectively. The RAPD primers OPD-18 and OPA-13 have recorded the highest resolution power and MI value. Overall, the RAPD marker-assisted molecular profiling produced highly polymorphic content. Next, the ISSR primers were used to evaluate the molecular diversity of banana cultivars. The ISSR markers showed an average of 79.62% polymorphism. Among all ISSR markers used, five ISSR primers-ISSR-810, ISSR-818, ISSR-826, ISSR-857, and ISSR-858 generated 100% polymorphism ( Table 4). The number of loci observed per primer varied from 3 to 9, with an average of 6.27 loci per primer. The PIC value for ISSR primer ranged from 0.12 to 0.42, with an average of 0.31. The parameters such as H, He, RP, and MI values measured using ISSR primers were: 0.44, 0.29, 6.39, and 2.26, respectively ( Table 5). The ISSR primers UBC-810, ISSR-841, and ISSR-827 were found to provide significant molecular markers with the highest resolution power and marker index value. Hence, the ISSR yielded a highly informative marker profile that successfully profiled selected genotypes of Musa spp.

Screening of diploid and triploid cultivars of banana (Musa spp) predominantly cultivated in
Additionally, SSR markers were also used to gain insights into selected genotypes of banana cultivars. The SSR marker produced polymorphic bands ranging from 1 to 5 loci per primer, and a total of 217 unique amplicons were recorded (   Table 5. SSR polymorphism. Na: no. of different alleles, Ne = NO. OF EFFECTIVE ALLeles = 1/(p^2 + q^2), I = Shannon's information index = − 1* (p * Ln (p) + q * Ln(q)), He: expected heterozygosity = 2 * p * q, uHe = unbiased expected heterozygosity = (2N/(2N-1)), RP = resolution power, MI = marker index. Identification and assignment of cultivar-specific markers for clonal fidelity analysis. Molecular screening and data analysis provided several polymorphic markers for diploid and triploid genotypes of the banana crop. This study identified several cultivar-specific biomarkers using RAPD, ISSR, and microsatellite markers ( Table 6, Fig. S1). We further analyzed the molecular data and assigned the biomarkers specific to the cultivar for clonal fidelity analysis in commercial agriculture. The RAPD primer OPC-08 has shown a particular fragment of 750 bp to Safedvelchi and Elavazhai cultivars (Fig. S1A). At the same time, the RAPD primer OPD-18 has shown a 1.4 kb specific fragment in cultivar Grand Nain, Ardhapuri, and Rasthali (Fig. S1B). Additionally, the RAPD profile of OPD-20 primer generated a unique band of 1.5 kb for the Neypoovan cultivar (Fig. S1C). The ISSR marker analysis of cultivars Grand Nain and Ardhapuri yielded a specific 0.9 kb fragment during fingerprinting using the ISSR-818 primer (Fig. S1D). The ISSR-818 primer was found to be located in the gene (KU977463.1) Musa acuminata AAA Group Constans-like 3b (COL3b) mRNA, complete CDS with E Value 0.062. Thus ISSR-818 was identified as a genome A specific genic biomarker. The cultivar Ankur yielded a 0.250 kb unique single fragment with an ISSR primer ISSR-827 and UBC-858 (Fig. S1E,G). The Grand Nain cultivar displayed a unique single specific amplicon of 0.7 kb with the primer ISSR-827 and a 0.  Table 6). The detailed annotation of the SSR and ISSR biomarkers in the banana www.nature.com/scientificreports/ genome is listed in Table 6. This set of molecular markers could be further developed as the biomarker for the clonal fidelity testing of tissue culture-raised plantlets of cultivars of commercial significance.
Estimation of genetic diversity using molecular clustering. The genetic diversity of bananas has been carried out using different molecular markers, and significant success has been made for analyzing commercial cultivars and some wild germplasm 34,35 . However, not much is known about the local germplasm, which harbors important traits for adaptation to local climatic conditions and small-holdings. In this regard, genetic diversity analysis was carried out in the diverse banana germplasm. Molecular clustering analysis of 20 banana genotypes based on RAPD fingerprinting resulted in two significant subgroups comprising ten genotypes in each group with 55% similarity (Fig. 1A). Group-I comprised banana genotypes with AA, AB, AAB, ABB, and AAA genomes, including Namarai, Ankur, Karpura Chakrakeli, Rajeli, Ney Poovan, Nendran, Ardhapuri, Grand Nain, Rasthali, and Neyvazhai. Within Group-I, cultivars Karpura Chakrakeli and Rajeli were found to be closely related with 88% of similarity. Group-II consisted of nine banana cultivars carrying AB, BB, ABB, and AAB genomes, which consisted of Safed Velchi, Elavazhai, Bhurkel, Bluggoe, Karpuravalli, Birbutia, Karimbontha, NRCB-3, and Borkal Baista. The cultivars in Group-II were found to have at least 71% similarity level. Whereas the cultivar Lamby was observed to have 37% uniqueness from other cultivars in Group-II. The phylogenetic analysis based on ISSR fingerprinting generated a dendrogram, which categorized 20 banana genotypes into two major groups in addition to the banana cultivars Namarai (AA) and Ankur (ABB) were clustered separately (Fig. 1A). Group I comprised banana cultivar of genome AB and BB type (Safed Velchi, Bhurkel, Karpuravalli, Borkal Baista, Bluggoe, NRCB-3, Elavazhai, Birbutia, Ney Poovan, Karimbontha and Lamby) with 70% of similarity level; while group II comprised of banana cultivars carrying AAA, AAB and ABB genomes, i.e., Karpura Chakrakeli, Rajeli, Nendran, Ardhapuri, Grand Nain, Rasthali, and Neyvazhai (Fig. 1B).
Consequently, we combined the RAPD, ISSR, and SSR fingerprinting data of twenty banana cultivars to construct a dendrogram (Fig. 1D). The combined molecular fingerprinting analysis revealed two major clusters, each comprised of 10 genotypes sharing 62% similarity. The first group contains Namarai, Ankur, Ardhapuri, Grand Nain, Ney Poovan, Karpura Chakrakeli, Rajeli, Neyvazhai, Nendran, and Rasthali. Among the genotypes in group I, Karpura Chakrakeli and Rajeli were genetically closer with 88% similarity, followed by genotypes www.nature.com/scientificreports/ Ardhapuri and Grand Nain with 81% similarity index. Whereas genotypes Neyvazhai, Namarai, and Ankur were grouped separately from other genotypes at a 47% dissimilarity level, Group-II comprised nine banana genotypes sharing 70% similarity. Lamby's genotype was separated at a 35% dissimilarity level from other genotypes in group II. The dendrogram obtained after collective clustering described the precise grouping of all twenty banana genotypes than the individual marker-based grouping. The results confirmed the applicability of a three-way molecular marker system in genotyping with higher confidence in estimating cultivar diversity among banana diploid and triploid genotypes.
Principle coordinate (PCA) and population structure analysis (PSA) revealed genetic distance among banana cultivars. The two-and three-dimensional PCA based on genetic variance was performed, which helped to categorize banana germplasm into two distinct groups similar to the groups or clusters obtained during dendrogram analysis of the combined molecular marker system ( Fig. 2A,B). PCA showed that the first three Eigenvalues explained 34% of the cumulative variation plotted to reveal diversity among banana germplasm. PCA corroborated cluster analysis results based on RAPD, ISSR, and SSR DNA fingerprinting. The cultivar Lamby was out-grouped and found genetically most distant. The population structure of 20 banana genotypes was estimated using SSR data. The structure analysis results based on a K-value of 1-10 revealed a peak of dk at K = 4 (Fig. 3A), proposing four major populations (Fig. 3B). The probability of membership threshold (C = 0.44), ten banana genotypes were allocated to SP3 (as 7 pure and 3 admixture), seven genotypes into SP2 (as 5 pure and 3 admixture), two genotypes into SP4, and one genotype into SP1. The pairwise genetic distance among the population was estimated (see Tables 7, 8 (Table 8). Additionally, we performed AMOVA for all 20 banana genotypes considering four sub-populations to support this evidence. A highly significant FST value of 0.23 (p > 0.001) was obtained, suggesting the presence of overall high genetic differentiation among and within populations. Further, it was observed that 23% of genetic variation separated the four sub-populations, and 77% of the total variation existed within the sub-populations (Table 9).
Volatile profiling of banana cultivars. Banana fruits are characterized by specific aroma profiles (volatilome), and considerable effort is needed to investigate aroma profiles during the ripening and post-ripening stages or storage of banana cultivars 26,36 . In the present study, we performed the volatile compounds profiling to understand the genotypic variation for volatilome of selected banana cultivars of the different genomic constitutions. The volatile compounds identified in banana fruits of nine different cultivars are depicted in Table 10. Maximum volatile compounds were identified in Borkal Baista i.e. 29, followed by 23 each in Rajeli, Ankur, and Karpuravalli, 20 in Bhurkel,16 in Birbutia, 10 in Ardhapuri, and 9 in Grand Nain. A total of fifty-four volatile compounds were identified from fruit samples of nine cultivars of banana and classified into nine unique chemical groups (Fig. 4, Table 10). Almost 56% of the total identified volatile compounds belonged to the ester group, while a minimum of about 2% belonged to carboxylic acid (Fig. 5). The ester compounds were predominantly observed in all the studied banana cultivars (Fig. 5). Among the nine banana cultivars, the highest number of volatile components, i.e., more than 20 i.e., approximately 37%, were recorded in fruits of the cultivars of Borkal Baista, Karpuravalli, Rajeli, Ankur, and Bhurkel. Therefore, these cultivars are suggested to be as rich in aroma and can be utilized for flavor enhancement of banana fruit by selective breeding. The highest number of ester compounds was recorded in Borkal Baista (18), followed by Ankur (17), Karapurvalli (17), Rajeli (12), Bhurkel (10), and Ardhapuri and Grand Nine (7 each) ( Table 10). In commercially grown cultivars, Ardhapuri and Grand Nine ester compounds contributed 70-78% of the volatilome suggesting that ester compounds are a major source of banana flavor and aroma and enhance the aesthetic value of the fruit. Another factor that contributed to the aroma was the alcohol groups. We found the distribution of alcohols in Birbutia (5, 31%), Bhurkel (5, 25%), Bluggoe (3, 34%) Rajeli (4, 18%), and Borkal Baista (3, 10%). The alcoholic compounds are also an important component of flavor in the cultivars desired for wine production. Additionally, aldehyde compounds were observed in Bluggoe, Borkal Baista, Bhurkel, Rajeli, and Ankur. Aldehyde compounds have an essential role in aroma 37 . Moreover, the ketone compounds have an important role in the banana aroma. In the present study, ketones were detected in five banana cultivars (Rajeli, Bhurkel, Karpuravalli, and Birbutia), contributing to the flavor of these cultivars. Although several compounds such as hydrocarbons, carboxylic acid, chlorinecontaining ethers, and diverse functional groups were detected in the volatiome analysis, previous studies suggested that these compounds do not contribute to banana aroma 26 .

Discussion
Genetic diversity and the development of genotype-specific markers are crucial for successful breeding and crop improvement. Banana breeding is a time-consuming and laborious process considering the requirements of time for crop cultivation, field size, and human resources. Therefore, the inclusion of marker-assisted breeding (MAB) can speed up the process of germplasm improvement and make it appealing to develop better performing commercial varieties 4,38 . Further, it can reduce the number of years consummated from pollination to preassessment of first fruit setting and yield, assessing several pollination cycles prior to screening for other biotic and abiotic stresses. Another advantage of MAB is the reduced cost of genetic screening and the wide range of sensing technology that can easily complement phenotyping 12  www.nature.com/scientificreports/ www.nature.com/scientificreports/ Chronically several limitations are faced by banana and other horticultural crop breeders as well as farmers from the tropics or subtropics, for example, with the widespread occurrence of misnomers 16,17 . However, misnomers are frequently grown as commercially cultivars, mislabelled with different names in local languages. To avoid such mislabeling and inappropriate branding, the characterization of misnomers (or synonyms) using molecular markers is essentially required. Thus a quick, simple, reproducible, and cost-effective method for cultivar identification and validation is required, which can be further developed as a certification method for cultured tissue plantlets of bananas. Moreover, it could also help in germplasm preservation and documentation of novel genetic resources 39 . Therefore, molecular markers hold promise and might help to encourage banana cultivation and smooth trade of authentic genetic material among banana-growing regions like the Marathwada region of  www.nature.com/scientificreports/ Maharashtra, India. The present study offers unique information on molecular markers and volatile profiles for commercially grown cultivars from the Marathwada region, a significant banana cultivation belt within India. This particular region has a growing concern with several misnomers. Hence, a desired molecular marker, a short unique genomic DNA sequence or fragment that carries a conserved inter-specific motif, would be beneficial for appropriate varietal identification. Moreover, such DNA markers possess minimum intra-specific separation to enable the classification of several cultivars and species 40 ; this approach is exploited in different species and cultivars of horticultural crops, including grapes 16,17 , pineapple 41 , and figs 42 . Our results have demonstrated that ISSR primer UBC-858 was found to be unique to Grand Nain, whereas the SSR maker CNMPF-13 was able to confirm the specific loci from the Ardhapuri cultivar, which could be further developed as biomarkers for DNA barcoding the plantlets produced through tissue culture for use in commercial cultivation or breeding programs. Since these DNA markers possessed strong discriminatory power, it could be helpful in the validation of uniformity among the plant population. The study showed that all the phenotypic characteristics in cultivated Musa sp. are geographical location and climate-specific. An earlier analysis of 68 banana accessions performed using RFLP of ITS fragments (digested with RsaI), produced steady, reliable, and distinctive patterns of polymorphic DNA in Musa sp. cultivars 43,44 . Likewise, ITS1-5.8S-ITS2 sequences 45 have also been successfully exploited in molecular diversity analysis of Musaceae.
The aesthetic value of fruits is primarily defined by the constituent volatiles (volatilome), which contribute to the unique aroma and flavor. Moreover, the aroma or flavor of fruits generates significant appeal driving the urge for consumer acceptance, consumption and usage 25 . The distinctive chemical nature of aroma and flavor are formed by combination of several volatile small molecules. In the case of banana, its agreeable and classic aromatic smell has been studied relatively recently, and there have been over 150 volatiles found to bequeath a unique aroma 32 .
In the present study, we report over 33% of the volatiles from fruits of nine banana cultivars. This volatiles belonged to several classes of small molecules like esters, ketones, terpenes, and aldehydes. Previously, isoamyl and isobutyl esters and ketones have been reported to be dominant in banana 26 . In our study, we observed that over 56% contribution to banana flavor is contributed by esters and in cultivar, Grand Nain esters contributed to 78% of the volatiles. Similarly, cultivars namely Ardhapuri, Karpurvalli, Ankur, and Borkee Baista represented significant portion of volatiles belonging to ester compounds. Suggesting dominance of the ester molecules in contribution towards characteristics aroma in these cultivars. Additionally, alcohols and carboxylic compounds were also significant constituents of banana aroma. The SPME method used to extract volatiles is simple, quick, robust, and solvent-free 24 . The method was efficient for the recovery of volatiles and could be optimized quickly for any fruit volatilome analysis 26,32,46 . Since some of the volatile compounds are reported to impart resistance against plant pathogens 47 , additional research is warranted on extensive spatial and temporal volatilome analysis from banana crops to establish the underlying mechanism of volatile biosynthesis and genetic control of resistance against certain pathogens 47 . In the future, novel technologies such as CRISPR-Cas 47,48 and nanotechnological applications 49-52 could help to enhance banana crop improvement.

Conclusions
Since banana is a polyploid and vegetatively propagated horticultural plant, genetic diversity and the development of genotype-specific markers are crucial for successful breeding and crop cultivation. The present study revealed a high polymorphism across the 20 banana genotypes evaluated with 11 RAPD, 11 ISSR, and 12 SSR primers. Phylogenetic and PCA clustered 20 banana genotypes into two significant clusters at 62% similarity level and 34% cumulative variation. AMOVA distributed 23% variation among the populations and 77% within the sub-populations with a significant FST value of 0.23, representing a high level of genetic differentiation. Interestingly, ISSR marker UBC-858 and SSR primer CNMPF-13 yielded a unique fingerprint for Grand Naine    www.nature.com/scientificreports/ and Ardhapuri cultivars, respectively, and could be utilized as cultivar-specific biomarkers for clonal fidelity testing in the tissue culture industry. The volatile profiling revealed the presence of several volatiles in banana cultivars and highlighted the role of ester compounds in the characteristic aroma. Thus, the food processing industry could exploit the contribution of ester-like compounds in banana flavor.

Data availability
The accessions analyzed during the current study are available in the ICAR-NRC Banana repository (https:// data. gov. in/ resou rces/ icar-publi cation-repos itory-date-nrc-banana-colle ction). The data generated and analyzed are presented in the figures or table of this submission. www.nature.com/scientificreports/